Measuring the Correlation of Personal Identity Documents in Structured Format

TL;DR

This paper presents a technique to extract data from structured digital identity documents and compute a normalized correlation score to verify their consistency, aiming to automate validation processes.

Contribution

The paper introduces a novel method for extracting and correlating data from structured digital identity documents to facilitate automated validation.

Findings

Effective correlation score calculation demonstrated

Supports automation of identity document validation

Potential to reduce manual verification efforts

Abstract

Personal identity documents play a major role in every citizen's life and the authorities responsible for validating them typically require human intervention to manually cross-check multiple documents belonging to an individual. The world is rapidly replacing physical documents with digital documents where every piece of data is stored digitally in a machine-readable and structured format. In this paper, we describe a technique to extract identity data from a structured data format and calculate a normalized correlation score for personal identity documents. Experimental results show that the proposed technique effectively calculates the correlation score for personal identity documents.